Prevalence and factors associated with unhealthy metabolic status according to body mass index: analysis of a national nutritional survey

Vera-Ponce V.J.; Zuzunaga-Montoya F.E.; Vásquez-Romero L.E.M.; Loayza-Castro J.A.; Iturregui Paucar C.R.; Vigil-Ventura E.; Gutiérrez De Carrillo C.I. · Diabetology and Metabolic Syndrome (2024) · DOI: 10.1186/s13098-024-01411-y

Resumen

Introduction: Although obesity substantially influences public health owing to related comorbidities, it has been discovered that the incidence of such issues is not directly related to obesity but to the patient’s unhealthy metabolic status (MUS) independent of the body mass index (BMI). Objectives: To describe the prevalence of UMS overall and according to BMI and determine the factors associated with it. Methods: A cross-sectional analytical study was used based on the analysis of secondary databases called the Life Stage Nutritional Surveillance Survey (VIANEV). Participants were selected in two stages, finally obtaining 885 participants. UMS was defined based on the criteria of the Adult Treatment Panel III used to define metabolic status in a set of 5 parameters, if the subject presented two or more alterations it was considered UMS. Six groups were formed according to BMI: metabolically healthy, average weight (MHNW) and unhealthy (MUNW), metabolically healthy, overweight (MHOW) and unhealthy (MUOW), metabolically healthy, obese (MHO) and unhealthy (MUO).). Results: The total prevalence of UMS was 73.11%, with MUNW, MUOW, and MUO being 47.90%, 80.34%, and 96.44%, respectively. Only 5.31% did not present any metabolic alteration. The multivariable analysis found variations globally according to sex, age, marital status, geographical region, smoking habit, and altitude. Conclusions: A high prevalence of UMS was observed in Peru, indicating that BMI alone is not a sufficient indicator of metabolic status. These findings suggest that strategies should be prioritized to address the growing problem of UMS, considering the particularities of each subpopulation and using a multifaceted approach that addresses modifiable and non-modifiable risk factors. © The Author(s) 2024.

Instituciones: Universidad Tecnológica del Perú; Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas